Wood defects classification using laws texture energy measures and supervised learning approach-Reference-Cited by-同舟云学术

Wood defects classification using laws texture energy measures and supervised learning approach

Published:2017-10 Issue: Volume:34 Page:125-135
ISSN:1474-0346
Container-title:Advanced Engineering Informatics
language:en
Short-container-title:Advanced Engineering Informatics

Author:

Kamal K.,Qayyum R.,Mathavan S.,Zafar T.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems

Reference37 articles.

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3. Automatic knot detection and measurements from X-ray CT images of wood: a review and validation of an improved algorithm on softwood samples;Longuetaud;Comput. Electron. Agric.,2012

4. Rule-driven defect detection in CT images of hardwood logs;Sarigul;Comput. Electron. Agric.,2003

5. H. Mu, D. Qi, Pattern recognition of wood defects types based on Hu invariant moments, in: 2nd International Congress on Image and Signal Processing (CISP), IEEE, Tianjin, October 17–19, 2009, pp. 1–5.

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